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Dr. Renato L. G. Cavalcante

R. L. G. Cavalcante received the electronics engineering degree from the Instituto Tecnologico de Aeronautica (ITA), Brazil, in 2002, and the M.E. and Ph.D. degrees in Communications and Integrated Systems from the Tokyo Institute of Technology, Japan, in 2006 and 2008, respectively. From April 2003 to April 2008, he was a recipient of the Japanese Government (MEXT) Scholarship. He is currently a Research Fellow with the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, Berlin, Germany. Previously, he held appointments as a Research Fellow with the University of Southampton, Southampton, U.K., and as a Research Associate with the University of Edinburgh, Edinburgh, U.K.

Dr. Cavalcante received the Excellent Paper Award from the IEICE in 2006 and the IEEE Signal Processing Society (Japan Chapter) Student Paper Award in 2008. He also co-authored the study that received the 2012 IEEE SPAWC Best Student Paper Award. His current interests are in signal processing for distributed systems, multiagent systems, convex analysis, machine learning, and wireless communications.

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Book Chapters

Stańczak, Sławomir and Keller, Alexander and Cavalcante, Renato LG and Binder, Nikolaus (2021). Long-term Perspectives: Machine Learning for Future Wireless Networks. Shaping Future 6G Networks: Needs, Impacts, and Technologies. John Wiley & Sons.


D. A. Awan, R.L.G. Cavalcante, M. Yukawa and S. Stanczak (2020). Adaptive Learning for Symbol Detection. Machine Learning for Future Wireless Communications. Wiley & IEEE Press, 15.


R. L. G. Cavalcante, S. Stanczak and I. Yamada (2014). Cooperative Cognitive Radios with Diffusion Networks. chapter Cognitive Radio and Sharing Unlicensed Spectrum in the book Mechanisms and Games for Dynamic Spectrum Allocation, Cambridge University Press, UK, 2014, 262-303.


Journal Publications

Miretti, Lorenzo and Cavalcante, Renato Lu'\is Garrido and Sta'nczak, Slawomir (2021). Channel Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces. IEEE Transactions on Signal Processing. IEEE, 3145–3159.


Miretti, Lorenzo and Cavalcante, Renato Lu'\is Garrido and Sta'nczak, Slawomir (2021). Channel Covariance Conversion and Modelling Using Infinite Dimensional Hilbert Spaces. IEEE Transactions on Signal Processing. IEEE, 3145–3159.


D. A. Awan, R. L.G. Cavalcante and S. Stanczak (2020). Robust Cell-Load Learning with a Small Sample Set. IEEE Transactions on Signal Processing (TSP), 68:270-283.


G. Bräutigam, R. L.G. Cavalcante, M. Kasparick, A. Keller and S. Stanczak (2020). AI and open interfaces: Key enablers for campus networks. ITU News Magazine - AI and Machine Learning in 5G, no. 5, p. 55, open access, Dec.


R. L.G. Cavalcante, Q. Liao and S. Stanczak (2019). Connections between spectral properties of asymptotic mappings and solutions to wireless network problems. IEEE Transactions on Signal Processing, Feb. 2019


B.-S. Shin, M. Yukawa, R. L. G. Cavalcante and A. Dekorsy (2018). Distributed Adaptive Learning with Multiple Kernels in Diffusion Networks. IEEE Transactions on Signal Processing, 5505-5519.


R.L.G. Cavalcante, M. Kasparick and S. Stanczak (2017). Max-Min Utility Optimization in Load Coupled Interference Networks. IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 705-716, Feb. 2017


Qi Liao and R. L. G. Cavalcante (2017). Improving Resource Efficiency with Partial Resource Muting for Future Wireless Networks. Proc. IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Oct. 2017


R.L.G. Cavalcante, S. Stanczak, J. Zhang and H. Zhuang (2016). Low complexity iterative algorithms for power estimation in ultra-dense load coupled networks. IEEE Trans. Signal Processing, vol. 64, no. 22, pp. 6058-6070, Nov. 2016


R.L.G. Cavalcante and Y. Shen and S. Stanczak (2016). Elementary Properties of Positive Concave Mappings With Applications to Network Planning and Optimization. IEEE Trans. Signal Processing, vol. 64, no. 7, pp. 1774-1783, April 2016


E. Pollakis, R.L.G. Cavalcante and S. Stanczak (2016). Traffic Demand-Aware Topology Control for Enhanced Energy-Efficiency of Cellular Networks. EURASIP Journal on Wireless Communications and Networks, vol. 2016, no. 1, pp. 1-17, Feb. 2016


M. Kasparick and R. L. G. Cavalcante and S. Valentin and S. Stanczak and M. Yukawa (2015). Kernel-Based Adaptive Online Reconstruction of Coverage Maps With Side Information. IEEE Transactions on Vehicular Technology, vol. 65, no. 7, pp. 5461-5473, July 2016 (also available at http://arxiv.org/abs/1404.0979)


R. Cavalcante and S. Stanczak and M. Schubert and A. Eisenblätter and U. Türke (2014). Toward Energy-Efficient 5G Wireless Communications Technologies. IEEE Signal Processing Magazine, vol. 31, no. 6, pp. 24-34, Nov. 2014


M. Vasirani, R. Kota, R. L. G. Cavalcante, S. Ossowski and N. R. Jennings (2013). An Agent-Based Approach to Virtual Power Plants of Wind Power Generators and Electric Vehicles. IEEE Transactions on Smart Grid , vol. 4, no. 3, pp. 1314-1322, Sept. 2013


R.L.G. Cavalcante and S. Stanczak (2013). A Distributed Subgradient Method for Dynamic Convex Optimization Problems under Noisy Information Exchange. IEEE Journal of Selected Topics in Signal Processing, vol. 7, no. 2, pp. 243-256, April 2013


Conference, Symposium, and Workshop Papers

K. Komuro and M. Yukawa and R. L. G. Cavalcante (2021). Distributed Sparse Optimization: Towards Global Optimality using Weakly Convex Regularizers. Proc. IEICE Signal Processing Symposium


Ismayilov, Rafail and Cavalcante, Renato LG and Sta'nczak, Sławomir (2021). Deep Learning Based Hybrid Precoding in Dual-Band Communication Systems. ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 4115–4119.


Ismayilov, Rafail and Cavalcante, Renato LG and Sta'nczak, Sławomir (2021). Deep Learning Beam Optimization in Millimeter-Wave Communication Systems. 2021 IEEE Statistical Signal Processing Workshop (SSP), 581–585.


Komuro, Kei and Yukawa, Masahiro and Cavalcante, Renato LG (2021). Distributed Sparse Optimization With Minimax Concave Regularization. 2021 IEEE Statistical Signal Processing Workshop (SSP), 31–35.


Manjunath, Ramya Panthangi and Schubert, Martin and Cavalcante, RL G and Boban, Mate and Zhou, Chan and Sta'nczak, Sławomir (2021). Proactive Application Rate Requirement Adaptation Mechanism for Sidelinks. 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 1–6.


Agrawal, Navneet and Cavalcante, Renato LG and Sta'nczak, Sławomir (2021). Adaptive Estimation of Angular Power Spectra for Time-Varying MIMO Channels. 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 96–100.


D.F. Külzer, S. Stanczak, R. L.G. Cavalcante and M. Botsov (2020). Predictive Resource Allocation for Automotive Applications using Interference Calculus. IEEE Globecom 2020, December 7-11, in Taipei, Taiwan


R. L. G. Cavalcante, Q. Liao and S. Stanczak (2020). Connections between spectral properties of asymptotic mappings and solutions to wireless network problems. ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing, , May 4-8, 2020 in Barcelona, Spain


R. L. G. Cavalcante and S. Stanczak (2020). Channel covariance estimation in multiuser massive MIMO systems with an approach based on infinite dimensional hilbert spaces. ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing, May 4-8, 2020 in Barcelona, Spain


M. Mehlhose, D. A. Awan, R. L.G. Cavalcante, M. Kurras and S. Stanczak (2020). Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform. accepted, IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020


J. Fink, R. L.G. Cavalcante and S. Stanczak (2020). Online Channel Estimation for Hybrid Beamforming Architectures. ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), Barcelona, Spain, 4-8 May 2020


R. L.G. Cavalcante and S. Stanczak (2020). Hybrid data and model driven algorithms for angular power spectrum estimation. IEEE GLOBECOM 2020, December 7 - 11, in Taipei, Taiwan


M. Mehlhose, D. A. Awan, R. L.G. Cavalcante, M. Kurras, S. Stanczak (2020). Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform. 45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, May 4-8, 2020, Barcelona, Spain


R. L. G. Cavalcante and S. Stanczak (2020). A hybrid model-data driven approach for the estimation of the angular power spectrum in massive MIMO systems. IEEE Statistical Signal Processing Workshop 2020, Rio de Janeiro, Brazil, 12th-15th July, 2020 (to appear)


J. Fink, D. Schäufele, M. Kasparick, R. L.G. Cavalcante and S. Stanczak (2019). Cooperative localization by set-theoretic estimation. 23rd International ITG Workshop on Smart Antennas (WSA), Vienna, Austria, 24-26 April 2019


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Contact

Dr. Renato L. G. Cavalcante
Fraunhofer Heinrich-Hertz-Institut
Einsteinufer 37
10587 Berlin